Since the topic of artificial intelligence (AI) came to be, humanity has debated the ethics and morals of creating artificial beings that dwarf human intelligence. Despite the debate, researchers continue to plug away, further expanding and applying it to a wide range of industries. In recent years and as the market continues to trend toward information dominance, AI is more and more being applied to Supply Chain Management (SCM).
In part four of our 5-part series on mathematical optimization, algorithms and business, we discuss the applicability of mathematical optimization in the business world and its ever-increasing importance. (Click here if you missed part three, Gartner's validation of algorithmic business as the new "it" word.)
It makes sense to incorporate expansion as part of your business model. Without continuous expansion, a business will likely stagnate and implode over time. A business that does not expand — rather, it maintains a steady rate of return — will be overtaken by things like inflation or other modes of economic flux. There's a real momentum to business, and should that be stilted, the push required to "get the ball rolling" again is often costlier than simply abandoning the failed venture. Naturally, any means of ensuring expansion will be sought.
Part one of our five-part series on algorithms, mathematical optimization and business answered the question "what is an algorithm" while part two dove into the definition of mathematical optimization. In the third post of the series, we will discuss why algorithms are quickly gaining press in the business world. Gartner has even coined this trend as the arrival of "algorithmic business." Peter Sondergaard, Senior Vice President at Gartner and Global Head of Research recently said "Algorithms are where the real value lies. Algorithms define action. Dynamic algorithms are the core of new customer interactions.” Let's dive deeper into the meaning of this statement
Modern data analysis is making acquisition and utilization of effective business algorithms realistic. When the data can be properly gathered and processed, best practices can be identified and redundant practices can be curtailed. In fact, IDC’s Worldwide Big Data and Analytics 2016 Predictions stated that “organizations that analyze all relevant data and deliver actionable information will achieve extra $430 billion in productivity gains over less analytically orients peers by 2020.